MLS Next Pro
Chicago Fire FC II crestChicago Fire FC II
1–2Finished
Philadelphia Union II crestPhiladelphia Union II

Chicago Fire FC II 1 x 2 Philadelphia Union II: prediction analysis

The model predicted correctly 3 of 5 settled markets.

Correct predictions

  • Double Chance: prediction Chicago Fire FC II or Philadelphia Union II; result Philadelphia Union II 1–2.
  • Over 2.5 goals: prediction Over 2.5; result 3 goals.
  • Both Teams to Score: prediction Yes; result Yes.

Incorrect predictions

  • 1x2: prediction Chicago Fire FC II; result Philadelphia Union II 1–2.
  • Over 9.5 corners: prediction Over 9.5; result 6 corners.

Final assessment: For this game, most settled predictions matched the observed results.

View the analysis published before kickoff

Before the game, the model Predora Market Median estimated a 51.4% probability of a win for Chicago Fire FC II, 21.4% for a draw, and 27.2% for a win for Philadelphia Union II.

Bookmaker consensus — The market makes Chicago the favorite, with odds ranging from 1.80 to 1.90 at 7 bookmakers with valid prices. The draw is in the 4.00–4.30 range, and Philadelphia is between 2.95 and 3.25. In relative terms (excluding the draw), the consensus assigns about 63.8% of the strength to the home side and 36.2% to the visitors.

What the signals say — The data analysis also favors Chicago, but less strongly: approximately 54.1% relative strength for the home side and 45.9% for the visitors. The main argument in Chicago’s favor is the home/away context (PPG 2.08 vs. 1.31 and xG differential 0.44 vs. -0.86). Recent form, on the other hand, favors Philadelphia (PPG 2.4 vs. 1.2), reducing the home side’s advantage in the models’ view.

Convergence and divergence — There is partial agreement: both point to Chicago as the favorite. However, the market is more confident than the signals, and this difference warrants attention. The draw accounts for about 21.9% of the 1X2 consensus and should be considered a significant possibility.

Uncertainty — Despite Chicago’s status as the favorite, Philadelphia’s strong recent form and the gap between the data analysis and the price suggest that the match should not be treated as a foregone conclusion.

Market 1x2

#68157126
Odds (Active Model) Fair odds according to the active model The odds calculated from the active model's estimated probability.
Formula: 1 ÷ Estimated probability
1.95 / 51.4%
Best Market Odds The implied probability of the bookmaker offering the highest odds for this outcome. A reference for comparison with the model's estimate.
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
1.84 / 54.3%
Edge (Mathematical Advantage) The difference between the model's probability and the implied probability of the highest-paying bookmaker. A positive value means the model estimates a higher probability than the odds imply; it does not guarantee a profit.
Formula: Probability − Implied probability (Book)
-3.0 p.p.
EV (Expected Value) A statistical estimate calculated from the Active Model's probability and the highest observed odds. If the Active Model's estimate is closer to the true probability than the odds-implied probability, positive EV may indicate estimated value at those odds. It is not a proven advantage, promise of profit, or guarantee of a result.
Formula: (Estimated probability × Odds) − 1
-5.5%

Odds Comparison

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Probability Models

ModelChicago Fire FC IIDrawPhiladelphia Union II
Predora Market Median 51.4% / 1.95 21.4% / 4.67 27.2% / 3.67

Market Double Chance

#68157126
Odds (Active Model) Fair odds according to the active model The odds calculated from the active model's estimated probability.
Formula: 1 ÷ Estimated probability
1.27 / 78.6%
Best Market Odds The implied probability of the bookmaker offering the highest odds for this outcome. A reference for comparison with the model's estimate.
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
1.36 / 73.4%
Edge (Mathematical Advantage) The difference between the model's probability and the implied probability of the highest-paying bookmaker. A positive value means the model estimates a higher probability than the odds imply; it does not guarantee a profit.
Formula: Probability − Implied probability (Book)
+5.2 p.p.
EV (Expected Value) A statistical estimate calculated from the Active Model's probability and the highest observed odds. If the Active Model's estimate is closer to the true probability than the odds-implied probability, positive EV may indicate estimated value at those odds. It is not a proven advantage, promise of profit, or guarantee of a result.
Formula: (Estimated probability × Odds) − 1
+7.1%

Odds Comparison

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Probability Models

Model1XX212
Predora Market Median 72.8% / 1.37 48.6% / 2.06 78.6% / 1.27

AI Analysis

Market and data partially aligned

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Team Comparison

Head-to-head (H2H) These statistics use the teams' most recent head-to-head games, generally from the last 10 to 15 years.H2H Last 5

Factor Chicago Fire FC II Philadelphia Union II
H2H: W/D/L (last 5) Results from the last 5 head-to-head games between the teams. Example: 3–1–1 = 3 wins, 1 draw, 1 loss for the team on the left.2-1-22-1-2
H2H: win % (home vs. away) (last 5) Head-to-head win percentage (last 5), split by home and away team. Example: the home team won 3 of 5 = 60%.40 %40 %

Outcome Strength (Season)

Game context (Home/Away)

Factor Chicago Fire FC II Home Philadelphia Union II Away
PPG (home/away) Average points per game in the relevant context (home team at home, away team away). Example: 6 points in 4 games = 1.5 points/game.Points per game in context (home team at home / away team away).2.08 pts/game1.31 pts/game
Win % (home/away) Win percentage in the relevant context (home for the home team, away for the away team). Example: 2 wins in 4 games = 50%.66.7 %38.5 %
Draw % (home/away) Draw percentage in the home/away context. Example: 1 draw in 4 games = 25%.8.3 %15.4 %
Goal difference (home/away) Average goal difference in context: goals scored minus goals conceded per game. Example: scored 6 and conceded 4 in 4 games → (6−4)/4 = +0.5.0.92 goals/game-0.36 goals/game
xG difference (home/away) Average xG difference in context: xG for minus xG against per game. Example: 1.4 − 1.1 = +0.3 xG/game.0.46 xG/game-0.86 xG/game

Season baseline (Overall) Temp

Factor Chicago Fire FC II Philadelphia Union II
PPG (overall) Average points per game this season (home + away). Example: 12 points in 8 games = 1.5 points/game.1.35 pts/game1.42 pts/game
Win % (overall) Win percentage this season (home + away). Example: 4 wins in 8 games = 50%.38.5 %42.3 %
Draw % (overall) Draw percentage this season (home + away). Example: 2 draws in 8 games = 25%.19.2 %15.4 %
Goal difference (overall) Average goal difference this season: (goals scored − goals conceded) / games. Example: 10−6 in 8 games → +0.5 per game.0.04 goals/game-0.11 goals/game
xG difference (overall) Average xG difference this season: xG for minus xG against per game. Example: 1.6 − 1.2 = +0.4 xG/game.0.15 xG/game-0.44 xG/game

Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5

Factor Chicago Fire FC II Philadelphia Union II
Form (last 5): W/D/L Results from the last 5 games: wins, draws, and losses. Example: 2–2–1 = 2 wins, 2 draws, 1 loss.2-0-34-0-1
PPG (last 5) Average points from the last 5 games. Example: 7 points in 5 games = 1.4 points/game.1.2 pts/game2.4 pts/game

Market Over 2.5 goals

#68157126
Odds (Active Model) Fair odds according to the active model The odds calculated from the active model's estimated probability.
Formula: 1 ÷ Estimated probability
1.34 / 74.4%
Best Market Odds The implied probability of the bookmaker offering the highest odds for this outcome. A reference for comparison with the model's estimate.
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
1.24 / 80.6%
Edge (Mathematical Advantage) The difference between the model's probability and the implied probability of the highest-paying bookmaker. A positive value means the model estimates a higher probability than the odds imply; it does not guarantee a profit.
Formula: Probability − Implied probability (Book)
-6.3 p.p.
EV (Expected Value) A statistical estimate calculated from the Active Model's probability and the highest observed odds. If the Active Model's estimate is closer to the true probability than the odds-implied probability, positive EV may indicate estimated value at those odds. It is not a proven advantage, promise of profit, or guarantee of a result.
Formula: (Estimated probability × Odds) − 1
-7.8%

Odds Comparison

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Probability Models

ModelOverUnder
Predora Market Median 74.4% / 1.34 25.6% / 3.90

Team Comparison

Predictions (AI) Prev

FactorGame
Potential: average goals Pregame estimate of total goals, based on historical data and AI, combining both teams. Example: 2.8 goals/game ≈ an estimate of 3 goals.3.58 goals
Over 2.5 potential Pregame estimated probability of 3+ goals, based on historical data and AI. Example: 52% estimates Over 2.5 in about 52 of 100 similar games.Pregame probability of over 2.5 goals73 %
Under 2.5 potential Pregame estimated probability of under 2.5 goals, based on historical data and AI. Example: 55% estimates Under 2.5 in about 55 of 100 similar games.Pregame probability of under 2.5 goals28 %

Season (baseline)

Game context (Home/Away)

Factor Chicago Fire FC II Home Philadelphia Union II Away
Goals scored (home/away) Average goals scored per game in the relevant context (home team at home, away team away). Example: 6 goals in 4 games = 1.5 goals/game.2.5 goals/game1.38 goals/game
Goals conceded (home/away) Average goals conceded per game in the home/away context. Example: 5 goals conceded in 4 games = 1.25 goals/game.1.42 goals/game1.85 goals/game
xG for (home/away) Average chance quality created per game (xG) in the home/away context. Example: 1.6 xG per game means the team’s shots add up to 1.6 expected goals per game on average.1.82 xG/game1.19 xG/game

Overall (Season) Temp

Factor Chicago Fire FC II Philadelphia Union II
Over 2.5 (season) Percentage of season games with over 2.5 goals. Example: 7 of 13 games = 54%.Season games with Over 2.5 %85 %54 %
Goals scored (overall) Average goals scored per game this season (home + away). Example: 20 goals in 13 games = 1.54 goals/game.1.85 goals/game1.31 goals/game
Shots on target / game Average shots on target per game this season (home + away). Example: 48 shots on target in 10 games = 4.8 per game.5.04 shots on target/game4.19 shots on target/game
Goals conceded (overall) Average goals conceded per game this season (home + away). Example: 15 goals in 13 games = 1.15 goals/game.1.77 goals/game1.46 goals/game

League (baseline) League

FactorLeague
League average goals Average goals per game in the league this season (competition baseline). Example: 2.68 goals/game ≈ 2–3 goals per game.Average league goals per game (baseline)3.35 goals/game

Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5

Factor Chicago Fire FC II Philadelphia Union II
Goals scored (last 5) Average goals scored per game in the last 5 games (recent form). Example: 9 goals in 5 games = 1.8 goals/game.1.2 goals/game2.4 goals/game
Goals conceded (last 5) Average goals conceded per game in the last 5 games (recent form). Example: 6 goals conceded in 5 games = 1.2 goals/game.2.2 goals/game2 goals/game

Head-to-head (H2H) These statistics use the teams' most recent head-to-head games, generally from the last 10 to 15 years.H2H Last 5

Factor Chicago Fire FC II Philadelphia Union II
H2H: Over 2.5 % (last 5) Percentage of the last 5 head-to-head games with over 2.5 goals. Example: 3 of 5 games = 60%.Recent H2H games with Over 2.560 %60 %

Market Both Teams to Score

#68157126
Odds (Active Model) Fair odds according to the active model The odds calculated from the active model's estimated probability.
Formula: 1 ÷ Estimated probability
1.39 / 72.1%
Best Market Odds The implied probability of the bookmaker offering the highest odds for this outcome. A reference for comparison with the model's estimate.
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
1.29 / 77.5%
Edge (Mathematical Advantage) The difference between the model's probability and the implied probability of the highest-paying bookmaker. A positive value means the model estimates a higher probability than the odds imply; it does not guarantee a profit.
Formula: Probability − Implied probability (Book)
-5.5 p.p.
EV (Expected Value) A statistical estimate calculated from the Active Model's probability and the highest observed odds. If the Active Model's estimate is closer to the true probability than the odds-implied probability, positive EV may indicate estimated value at those odds. It is not a proven advantage, promise of profit, or guarantee of a result.
Formula: (Estimated probability × Odds) − 1
-7.1%

Odds Comparison

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Probability Models

ModelYesNo
Predora Market Median 72.1% / 1.39 27.9% / 3.58

Team Comparison

Predictions (AI) Prev

FactorGame
Potential: BTTS (%) Pregame estimated probability of both teams scoring, based on historical data and AI. Example: 58% estimates that about 58 of 100 similar games would have goals from both teams.56 %
Over 2.5 potential Pregame estimated probability of 3+ goals, based on historical data and AI. Example: 52% estimates Over 2.5 in about 52 of 100 similar games.Pregame probability of over 2.5 goals73 %

Season baseline (Season)

Indicators associated with more BTTS outcomes

Factor Chicago Fire FC II Philadelphia Union II
BTTS (season) % Percentage of season games in which both teams scored. Example: 7 of 12 games = 58%.65 %54 %
Games scoring 1+ goal % (season) Percentage of season games in which the team scored at least 1 goal. Example: scored in 10 of 12 games = 83%.77 %69 %
Games conceding 1+ goal % (season) Percentage of season games in which the team conceded at least 1 goal. Example: conceded in 8 of 12 games = 67%.81 %81 %

Indicators associated with fewer BTTS outcomes

Factor Chicago Fire FC II Philadelphia Union II
Clean sheet % (season) Percentage of clean sheets, a factor associated with fewer Both Teams to Score outcomes. Example: 4 clean sheets in 12 games = 33%.19 %19 %
Failed to score % (season) Percentage of games without scoring, a factor associated with fewer Both Teams to Score outcomes. Example: no goals scored in 3 of 12 games = 25%.23 %31 %

Recent form (Last 5) These statistics cover the team's last 5 games, regardless of league or season.Last 5

Factor Chicago Fire FC II Philadelphia Union II
Games scoring 1+ goal % (last 5) Percentage of the last 5 games in which the team scored at least 1 goal. Example: scored in 4 of 5 = 80%.60 %100 %
Games conceding 1+ goal % (last 5) Percentage of the last 5 games in which the team conceded at least 1 goal. Example: conceded in 3 of 5 = 60%.80 %80 %

Head-to-head (H2H) These statistics use the teams' most recent head-to-head games, generally from the last 10 to 15 years.H2H Last 5

FactorHead-to-head (H2H)
H2H: BTTS % (last 5) Percentage of the last 5 head-to-head games in which both teams scored. Example: 3 of 5 games = 60%.80 %

Market Over 9.5 corners

#68157126
Odds (Active Model) Fair odds according to the active model The odds calculated from the active model's estimated probability.
Formula: 1 ÷ Estimated probability
1.88 / 53.3%
Best Market Odds The implied probability of the bookmaker offering the highest odds for this outcome. A reference for comparison with the model's estimate.
Formula: 1 ÷ Best market odds (highest-paying bookmaker)
1.78 / 56.3%
Edge (Mathematical Advantage) The difference between the model's probability and the implied probability of the highest-paying bookmaker. A positive value means the model estimates a higher probability than the odds imply; it does not guarantee a profit.
Formula: Probability − Implied probability (Book)
-3.0 p.p.
EV (Expected Value) A statistical estimate calculated from the Active Model's probability and the highest observed odds. If the Active Model's estimate is closer to the true probability than the odds-implied probability, positive EV may indicate estimated value at those odds. It is not a proven advantage, promise of profit, or guarantee of a result.
Formula: (Estimated probability × Odds) − 1
-5.4%

Odds Comparison

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Probability Models

ModelOverUnder
Predora Market Median 53.3% / 1.88 46.7% / 2.14

Team Comparison

Predictions (AI) Prev

FactorGame
Potential: average corners Pregame estimate of total corners, based on historical data and AI. Example: 10.2 corners ≈ an estimate of 10 corners.8.64 corners
Potential Over 9.5 corners (%) Pregame estimated probability of 10+ corners, based on historical data and AI. Example: 58% estimates Over 9.5 in about 58 of 100 similar games.51 %

Season (baseline)

Game context (Home/Away)

Factor Chicago Fire FC II Home Philadelphia Union II Away
Corners for (home/away) Average corners won per game in context (home team at home, away team away). Example: 24 corners in 6 games = 4.0 per game.5.18 corners/game3.46 corners/game
Total corners (home/away) Average total corners per game in context (both teams combined). Example: 60 corners in 6 games = 10.0 per game.9.82 corners/game8.61 corners/game

Overall (Season) Temp

Factor Chicago Fire FC II Philadelphia Union II
Corners for (overall) Average corners won per game this season (home + away). Example: 40 in 10 games = 4.0 per game.5.44 corners/game3.69 corners/game
Total corners (overall) Average total corners per game this season (home + away). Example: 105 in 10 games = 10.5 per game.10 corners/game9.15 corners/game

League (baseline) League

FactorLeague
League average corners (corners/game) Average corners per game in the league this season (competition baseline). Example: 9.3 corners/game ≈ 9–10 corners per game.9.57 corners/game

Cards

Team Comparison

Predictions (AI) Prev

FactorGame
Potential: average cards Pregame estimate of total cards, based on historical data and AI. Example: 4.8 cards ≈ an estimate of 5 cards.3.48 cards/game

Season baseline (Season) Temp

Factor Chicago Fire FC II Philadelphia Union II
Total cards (average) Average cards per game this season (home + away). Example: 18 cards in 6 games = 3.0 cards/game.1.46 cards/game2.19 cards/game
Over 4.5 cards % Probability (or observed percentage, depending on the source) of 5+ cards in the game. Example: 60% estimates Over 4.5 in about 60 of 100 similar games.23 %35 %

League (baseline) League

FactorLeague
League average cards Average cards per game in the league this season (competition baseline). Example: 4.3 cards/game ≈ 4–5 cards per game.3.23 cards/game